1. Field
Apparatuses and methods consistent with exemplary embodiments relate to estimating a position of a mobile object which moves on a road.
2. Description of the Related Art
A robot may be an automatically controlled figure having a person-like appearance and operates like a human-being through a machine inside the figure. However, recently, any device which autonomously performs a task regardless of the appearance is commonly called a robot. In particular, a mobile robot has drawn a lot of attention because the mobile robot may work in extreme environments or dangerous regions. Furthermore, the mobile robots for home use, such as cleaning robots, are widely used.
In order for a mobile robot to automatically perform various tasks, the mobile robot needs to be capable of performing autonomous movement. In order to solve the autonomous movement issue of the robot, first, the robot should be able to determine its current position. That is, in order to for mobile robot to autonomously move while performing tasks, localization for self position recognition is essential. One type of localization technology is simultaneous localization and mapping (SLAM). The SLAM refers to a method of estimating the robot's absolute position while writing a map corresponding to a task-performing space by detecting surrounding environment information and processing the obtained information.
For position estimation of the existing robot, various sensors such as a global positioning system (GPS), light detection and ranging (LIDAR), and a camera have been applied along with odometry. However, the GPS may have frequent errors and operate only in an outdoor environment, and LIDAR may fail to estimate the robot's position due to non-reflection of light when used in a wide-open outdoor environment without any structures for the light to be reflected.